Part2- Master Generative AI and RAG- Hands On Step 1: Load & Chunk Documents using LangChain скачать в хорошем качестве

Part2- Master Generative AI and RAG- Hands On Step 1: Load & Chunk Documents using LangChain

Welcome to Part-2 of our Retrieval-Augmented Generation (RAG) tutorial series, where we take a hands-on approach to implementing RAG using LangChain and AWS Bedrock. github link for this tutoriol https://github.com/deekshanee/langcha... 🔹 What You’ll Learn in This Video: ✅ Step 1: Load Documents – Ingest data from various sources efficiently ✅ Step 2: Chunking Documents – Preprocess and segment text for optimal retrieval ✅ LangChain Document Loaders – Supported formats and best practices ✅ Text Splitting Strategies – Chunk size, overlap, and impact on retrieval This tutorial is designed for developers, AI enthusiasts, and engineers looking to build their own RAG-powered applications. 📌 Stay tuned for upcoming parts where we cover embedding, vector stores, and querying! 🔔 Like, Subscribe & Share to stay updated on the next steps. Let me know your thoughts in the comments! #RetrievalAugmentedGeneration #RAG #LangChain #AWSBedrock #GenerativeAI #AI #MachineLearning #VectorSearch #DocumentProcessing